Development and Validation of a Dynamic 48-Hour In-Hospital Mortality Risk Stratification for COVID-19 in a UK Teaching Hospital: A Retrospective Cohort Study (preprint)

ABSTRACT

Background: While numerous point-of-admission disease severity models for COVID-19 have been proposed, disease stratification that accounts for changes in a patient’s condition while in hospital is urgently needed to facilitate patient management and resource allocation.Methods: We developed a prognostic model for 48-hour in-hospital mortality using 473 consecutive patients with COVID-19 presenting to a UK hospital between March 1 and September 12, 2020; and temporally validated using data on 405 patients presenting between September 13, 2020 and January 3, 2021.The primary outcome was all-cause in-hospital mortality. We additionally considered the competing risks of discharge from hospital and transfer to a tertiary Intensive Care Unit for extracorporeal membrane oxygenation. We adopted a landmarking approach to dynamic prediction that accounts for competing risks and informative missingness, and selected predictors using penalised regression. The model estimates, at any point during a hospital visit, the probability of in-hospital mortality during the next 48 hours.Results: Our final model includes age, Clinical Frailty Scale score, heart rate, respiratory rate, SpO2/FiO2 ratio, white cell count, presence of acidosis (pH < 7.35) and Interleukin-6. Internal validation achieved an AUROC of 0.90 (95% CI 0.87–0.93) and temporal validation gave an AUROC of 0.91 (95% CI 0.88-0.95). Interpretation: Our model uniquely incorporates both static risk factors (e.g. age) and evolving clinical and laboratory data, to provide a dynamic risk prediction model that adapts to both sudden and gradual changes in an individual patient’s clinical condition. External validation outside the study hospital will be required before adoption.Funding: NIHR Cambridge Biomedical Research Centre, UKRI Medical Research CouncilDeclaration of Interest None to declare. Ethical Approval The study was approved by a UK Health Research Authority ethics committee (20/WM/0125). Patient consent was waived because the de-identified data presented here were collected during routine clinical practice; there was no requirement for informed consent.